Computer Vision 1

for MSc in Artificial Intelligence at University of Amsterdam

About

Digital cameras, ubiquitously present in the form of webcams, cell phones, and professional cameras, have provided enormous streams of data and means for communication and interaction. In this course, image understanding is addressed with the focus on core vision tasks of scene understanding and object recognition.

A broad range of techniques are studied on how computers can understand the visual world of humans including image formation and filtering, features (color and shape invariants, interest point detectors, descriptors, SIFT, HoG), visual information representation (vector space, statistical models, bag-of-words), learning and classification (nearest neighbor, kernel density estimation, SVM), dimension reduction (PCA, LDA and SVD), object detection and classification, object tracking (mean-shift, Kalman), and user interaction (active learning).

The class is taught by Prof. Theo Gevers, A/Prof. Thomas Mensink, A/Prof Pascal Mettes, and A/Prof Shaodi You. The teaching assistant team includes Anil Baslamisli, Hoang-An Le, William Thong, Mert Kilickaya, Wei Zeng, Jian Han, and Yunlu Chen, Rick Groenendijk, Partha Das.

Past classes are archived here: Spring 2019

Instructors

Teaching Assistants

Schedule

Following is the tentative schedule and some practical information. Please keep an eye on Datanose, Canvas, and Piazza for up-to-date changes.

Lecture 1: Introduction

SP H0.08 | 5pm-7pm | September 02, 2019

Warm-up: MATLAB tutorial

5pm-7pm | September 05, 2019

Lecture 2: Image Formation

SP H0.008 | 5pm-7pm | September 09, 2019

Exercise 1

SP C1.110 | 1pm-3pm | September 10, 2019

Lab1: Photometric Stereo and Color

5pm-7pm | September 12, 2019

Lecture 3: Color and Image Processing

SP H0.008 | 5pm-7pm | September 16, 2019

Exercise 2

SP C1.110 | 1pm-3pm | September 17, 2019

Lab2: Neighborhood Processing: Gabor and Gaussian Filters

5pm-7pm | September 19, 2019

Lecture 4: Features, Detections, Motions and Classification

SP H0.008 | 5pm-7pm | September 23, 2019

Exercise 3

SP C0.05 | 1pm-3pm | September 24, 2019

Lab3: Optical Flow and Harris Corner Detector

5pm-7pm | September 26, 2019

Lecture 5: Object recognition: BoW and ConvNets

SP H0.08 | 5pm-7pm | September 30, 2019

Exercise 4

SP C1.110 | 1pm-3pm | October 01, 2019

Lab4: Image Alignment and Stitching

5pm-7pm | October 03, 2019

Lecture 6: Object Detection, Stereo and 3D Reconstruction

SP H0.08 | 5pm-7pm | October 07, 2019

Exercise 5

SP C1.110 | 1pm-3pm | October 08, 2019

Project: Building an Object Classification System | Part 1: Bag of Words

5pm-7pm | October 10, 2019

Lecture 7: Applications

SP H0.08 | 5pm-7pm | October 14, 2019

Exercise 6

SP REC C0.01 | 1pm-3pm | October 15, 2019

Project: Building an Object Classification System | Part 2: Convolution Neural Networks

5pm-7pm | October 17, 2019

Contact

The good place to ask questions is Piazza